Displaying 5 results from an estimated 5 matches for "dimorphism".
2011 Sep 02
0
Standard errors of sexual dimorphism?
Hello!
I am working on a manuscript on sexual dimorphism in an aquatic
invertebrate, where we have estimated sexual dimorphism (SD) for 7 different
traits in four populations (a total of 28 SD-estimates). We have used the
following formula for estimating SD: 100 * (mean male trait value - mean
female trait value)/overall trait mean).
Then, we have used...
2004 Mar 17
1
ANCOVA when you don't know factor levels
...have smaller horns and larger wings,
and rely on mobility to find mates before the guys with the big horns
turn up and beat them up. Normally what we do to see if this is
happening is to plot a scatter plot of horn length vs body size. If
it's a simple straight line relationship then no dimorphism, but if
it's either a line with an obvious change of slope or two separate
lines then you've got a dimorphic animal.
If you've just got a change of slope then it's relatively easy to test
for significance by breakpoint regression, which will also tell you the
body size at w...
2004 Sep 13
2
Mixture Analysis
Dear all,
Does anyone know if the mixture analysis (i.e : sexual dimorphism, age group,…) can be done with R software ? Thanks for your help
Dan
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2006 May 20
1
ANCOVA, Ops.factor, singular fit???
I'm trying to perform ANCOVAs in R 1.14, on a Mac OS X, but I can't figure out
what I am doing wrong. Essentially, I'm testing whether a number of
quantitative dental measurements (the response variables in each ANCOVA) show
sexual dimorphism (the sexes are the groups) independently of the animal's size
(the concomitant variable). I have attached a 13-column matrix as a data frame
(so far, so good). But then I tried to do this:
>model<-lm(ln2~sex*ln1)
or this:
>model<-lm(ln2~sex+ln1)
and got this:
Warning message:...
2002 Nov 26
0
nlme: gnls with weights and correlation arguments
...neralized non-linear
least squares function within the nlme library, to study evolutionary
questions where correlations between traits at the species level are
non-independent because of the evolutionary relatedness of the species.
Specifically, they're using a non-linear function (log(sexual dimorphism)
~ log(a + b*variation in mating opportunities), an exponential spatial
correlation function that depends on the phylogenetic distance between
species [I hacked the library a little bit to allow one to specify a
distance matrix directly, rather than specifying spatial positions], and a
weight fun...